Method and system for aggregating video content

ABSTRACT

Aspects of the subject disclosure may include, for example, systems and methods aggregating video content and adjusting the aggregate video content according to a training model. The adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images. The first subset of the images is determined by the training model based on a plurality of categories corresponding to a plurality of events. The illustrative embodiments also include presenting the adjusted aggregate video content and receiving identifications for the first subset of the images in the aggregate video content. Further, the illustrative embodiments include adjusting the training model according to the identifications and providing the adjusted training model to a network device. Other embodiments are disclosed.

FIELD OF THE DISCLOSURE

The subject disclosure relates to a method and system for aggregatingvideo content.

BACKGROUND

Both commercial and residential premises have “smart home” capabilitiesthat include sensors and cameras that provide information to a “smarthome” subscriber associated with the premises. Such information caninclude images from the cameras, motion sensor information, heat sensorinformation, appliance sensor information, acoustic sensor information,etc. The large amount of information can be aggregated by a premisesdevice and presented to the “smart home” subscriber for review.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIGS. 1-2 depict illustrative embodiments of systems for aggregatingvideo content;

FIGS. 3-7 depict illustrative embodiments of user interfaces that areused in systems for aggregating video content;

FIG. 8 depicts an illustrative embodiment of a method for aggregatingvideo content used in portions of the systems described in FIGS. 1-2;

FIGS. 9-10 depict illustrative embodiments of communication systems thatprovide services for aggregating video content;

FIG. 11 depicts an illustrative embodiment of a web portal forinteracting with the communication systems of aggregating video content;

FIG. 12 depicts an illustrative embodiment of a communication deviceused in systems for aggregating video content; and

FIG. 13 is a diagrammatic representation of a machine in the form of acomputer system within which a set of instructions, when executed, maycause the machine to perform any one or more of the methods describedherein.

DETAILED DESCRIPTION

The subject disclosure describes, among other things, illustrativeembodiments for aggregating video content and adjusting the aggregatevideo content according to a training model. The adjusted aggregatevideo content comprises a first subset of the images and does notcomprise a second subset of the images. The first subset of the imagesis determined by the training model based on a plurality of categoriescorresponding to a plurality of events. The illustrative embodimentsalso include presenting the adjusted aggregate video content andreceiving identifications for the first subset of the images in theaggregate video content. Further, the illustrative embodiments includeadjusting the training model according to the identifications andproviding the adjusted training model to a network device. Otherembodiments are described in the subject disclosure.

One or more aspects of the subject disclosure include a devicecomprising a processing system including a processor and a memory thatstores executable instructions that, when executed by the processingsystem, facilitate performance of operations. The operations can includereceiving video content from each of a plurality of cameras orientedtoward a current premises resulting in a plurality of video content. Theplurality of video content comprises images of a plurality of events.Further operations can include aggregating the plurality of videocontent to generate aggregate video content and applying a selectedtraining model to the aggregate video content resulting in adjustedaggregate video content. The adjusted aggregate video content comprisesa first subset of the images and does not comprise a second subset ofthe images. The first subset of the images is determined by the selectedtraining model based on a plurality of categories corresponding to theplurality of events. Additional operations can include presenting theadjusted aggregate video content and receiving user-generated input forthe adjusted aggregate video content. The user-generated input providesidentifications for the first subset of the images in the aggregatevideo content. Also, the operations can include adjusting the selectedtraining model according to the user-generated input resulting in anadjusted training model and providing the adjusted training model to anetwork device.

One or more aspects of the subject disclosure include a machine-readablestorage medium, comprising executable instructions that, when executedby a processing system including a processor, facilitate performance ofoperations. Operations can include receiving a plurality of videocontent associated with a current premises. The plurality of videocontent comprises images of a plurality of events. Further operationscan include aggregating the plurality of video content to generateaggregate video content and applying a selected training model to theaggregate video content resulting in adjusted aggregate video content.The adjusted aggregate video content comprises a first subset of theimages and does not comprise a second subset of the images. The firstsubset of the images is determined by the selected training model basedon a plurality of categories corresponding to the plurality of events.The selected training model is selected according to a plurality ofcharacteristics of the current premises. Additional operations caninclude presenting the adjusted aggregate video content and receivinguser-generated input for the adjusted aggregate video content. Theuser-generated input provides identifications for the first subset ofthe images in the aggregate video content. Also, the operations caninclude adjusting the selected training model according to theuser-generated input resulting in an adjusted training model andproviding the adjusted training model to a network device.

One or more aspects of the subject disclosure include a method. Themethod can include receiving, by a processing system including aprocessor, video content from each of a plurality of cameras orientedtoward a current premises. The plurality of video content comprisesimages of a plurality of events. Further, the method can includeaggregating, by the processing system, the plurality of video content togenerate aggregate video content. In addition, the method can includeadjusting, by the processing system, the aggregate video contentresulting in adjusted aggregate video content according to a trainingmodel. The adjusted aggregate video content comprises a first subset ofthe images and does not comprise a second subset of the images. Thefirst subset of the images is determined by the training model based ona plurality of categories corresponding to the plurality of events.Also, the method can include presenting, by the processing system, theadjusted aggregate video content and receiving, by the processingsystem, identifications for the first subset of the images in theaggregate video content. Further, the method can include adjusting, bythe processing system, the training model according to theidentifications resulting in an adjusted training model and providing,by the processing system, the adjusted training model to a networkdevice.

FIGS. 1-2 depict illustrative embodiments of systems 100 and 200 foraggregating video content. Referring to FIG. 1, in one or moreembodiments, premises 102 and 104, such as a home, commercial building,or government office, may have an arrangement of surveillance cameras106, 108, 116, and 118 that captures video content of the premises andits surroundings throughout a day. The video content can be in the formof images, portions of video, audio, or a combination thereof.

In one or more embodiments, a camera 106 and 116 can capture and recordvideo content near the front door of the premises. Camera 108 and 118can capture and record video content of the surroundings of thepremises. Further, surveillance cameras 110 and 120 within aneighborhood of the premises 102 and 104 can also capture and recordvideo content of the surroundings of the premises 102 and 104.Surveillance cameras 110 and 120 may be fixed on a city lamp post 112and can be operated by a third party such as a local municipalityagency. The cameras 106, 108, 116, and 118 can store captured videocontent in a database accessible by a premises device that controlsoperation of the cameras 106, 108, 116, and 118. Further, cameras 110and 120 can forward captured video content of the surroundings of thepremises 102 and 104 over a communication network to the databaseaccessible by the premises device. Note, the database can be located onthe premises 102 and 104 or in a cloud network.

In one or more embodiments, the system 100 records video contentcaptured by cameras 106, 108, 110, 116, 118, and 120 throughout eachday. The premises device can present the entirety of the captured videocontent to a user of the system 100 (e.g. the premises owner) to review.However, reviewing 24 hours of video from each camera 106, 108, 110,116, 118, and 120 is a cumbersome task for the user. Thus, system 100reduces the amount of video content for a user to review using thetechniques described herein.

In one or more embodiments, the system 100 detects whether an event inthe captured video content occurred during a time period, using apremises computing device (e.g. premises device). An event can bemovement of an object. For example, the premises device can detect aperson 114 and 122 moving in the surroundings of the premises. Thus, thepremises device can provide the user to review recorded video contentthat only contains events (e.g. motion of a person). The premises devicecan use image processing techniques to detect motion of objects in thecaptured aggregate video content to adjust or reduce the aggregate videocontent.

However, the amount of video content to review by the user can still becumbersome given that there are multiple cameras each have multipleevents to review. Therefore, the premises device adjusts or reduces theamount of the video content by identifying and categorizing the events.That is, by premises device classifying events into categories, and onlypresenting the user to review events from certain categories, reducesthe amount of captured video content for the user to review. Forexample, the premises device can be configured to detect not onlymovement of person 114 but also whether that person 114 is known andregularly visits the premises 102 and 104. If so, the premises devicecan discard video content containing the person 114 for the user toreview. For example, person 114 can be a mailman. Thus, responsive todetecting that the person 114 is the mailman within the captured videocontent, the premises device can discard the portion of the videocontent containing images of the mailman 114. However, if the premisesdevice detects a person 122 within the captured video content, but isnot able to identify the person 122 (i.e. a stranger) then the premisesdevice presents the portion of the video content containing images ofperson 122 to the user for review.

Referring to FIG. 2, system 200 aggregates video content captured bypremises surveillance cameras for review by a user. In one or moreembodiments, each premises 202 and 204 can have multiple surveillancecameras 212, 214, 222, and 224 as part of a “smart” home system 206 and208. A “smart” home system is the use of data collected from cameras andsensors placed within and surrounding a premises to automaticallyprovide services to improve the user's quality of life. Such a “smart”home system can be controlled or managed by a premises device 219 and229.

The premises device 219 and 229 are communicatively coupled over acommunication network 210 and 220 to the cameras 212, 214, 222, and 224as well as motion sensors 216, 218, 226, and 228. The premises device219 and 229 collects data from and manages or controls cameras 212, 214,222, and 224 and motion sensors 216, 218, 226, and 228 over thecommunication network 210 and 220. Further, the communication network210 and 220 can be a wireless network (e.g. WiFi) or a wired network(e.g. Ethernet). Further, the premises device 219 and 229 can becommunicatively coupled to a network device such as a computer server232 over a communication network (e.g. Internet, cloud network, etc.).

In one or more embodiments, the surveillance cameras 212, 214, 222, and224 capture video content of the premises 202 and 204 and itssurroundings. The premises device 219 and 229 aggregates the videocontent for presentation to the user for review. However, the amount ofaggregate video content can be cumbersome for the user to review. Thus,premises device 219 and 229 adjusts the aggregate video content byreducing the amount of aggregate video content for the user to review.Prior to reducing the aggregate video content, the premises device 219and 229 identifies or detects events in the aggregate video content. Insome embodiments, the premises device 219 and 229 can detect events bydetecting motion with a portion of the aggregate video content. In otherembodiments, the premises device 219 and 229 detects motion using imageprocessing techniques on the aggregate video content. In furtherembodiments, the premises device 219 and 229 can use data from motionsensors 216, 218, 226 and 228 that are coupled to the premises device219 and 229 to detect events within the aggregate video content. Thatis, the motions sensors 216, 218, 226 and 228 can be located near thecameras 212, 214, 222, and 224 such that the area that each sensor candetect motion in an area that overlaps with the viewing area of eachcamera. Further, the motion sensors 216, 218, 226, and 228 can providethe premises device 219 and 229 with a time period that a sensor 216,218, 226, and 228 detects motion for the premises device 219 and 229 toidentify the portion of the video content captured by a camera 212, 214,222, and 224 over same time period as an event.

In one or more embodiments, the aggregate video content that correspondsto the identified events can be too cumbersome for a user to review.Thus, the premises device 219 and 229 can apply a training model to theaggregate video content to adjust or reduce the aggregate video content.A training model identifies events that do not need to be reviewed bythe user because they are ordinary events due to the characteristics ofthe premises 202 and 204 and its neighborhood. For example, if anapplied training model is for an urban environment, then a taxi cabparked in front of the premises 202 and 204 would be classified as atypical event that would be discarded from the adjusted aggregate videocontent presented to the user to review. However, if the appliedtraining model is for a suburban environment, then a taxi cab parked infront of the premises 202 and 204 would be classified as not a typicalevent that is kept in the adjusted aggregate video content presented tothe user to review.

In one or more embodiments, the training model can be provided to thepremises device 219 229 by the server 232 according to characteristicsof the premises 202 and 204. In some embodiments, the server 232 canprovide multiple training models to premises device 219 and 229. Thepremises device 219 and 229 can list the training models on a userinterface of a communication device 213 for the user to select to applyto the aggregate video content. In further embodiments, one or more ofthe multiple training models is from a third party premises device andthe third party premises is associated with the premises. For example,one of the training models received by premises device 219 from theserver 232 may have been generated and provided by premises device 229located within a premises 204, which is a neighbor to premises 202. Thetraining model can include identifications of images that can be used bythe premises device 219 to adjust/reduce the aggregate video content.For example, the training model provided by premises device 229 mayinclude identification of a new neighbor. When premises 219 applies thetraining model with the identification of the new neighbor to theaggregate video content, the premises device 219 can discard images thatcontain the new neighbor from the aggregate video content, therebyreducing the aggregate video content and lessening the burden of theuser's review.

In one or more embodiments, applying of the training model, by thepremises device 219 and 229, to the aggregate video content includesanalyzing the images of the events and classifying the images of eventsinto categories. Analyzing the images can include identifying motion ofan object, such as a person, in one of the images. Classifying theimages into categories can include determining whether the person can beassociated with the premises 202 and 204. For example, the person couldbe the neighborhood mailman. The premises device 219 and 229 can usefacial recognition or image processing techniques to determine whetherthe person is associated with the premises 202 and 204. Further, if itis determined that the person is not associated with the premises 202,then an alarm notification can be transmitted by the premises device 219to the user's communication device 213 notifying the user.

In one or more embodiments, after adjusting/reducing the aggregate videocontent by applying the training model, the premises device 219 and 229can determine a size of the adjusted/reduced aggregate video content isabove predetermined threshold. If it is determined that the size of theadjusted/reduced aggregate video content is above the predeterminedthreshold, then the premises device 219 and 229 can apply anothertraining model to further adjust/reduce the aggregate video content. Thepremises device 219 and 229 can continue to apply training models untilthe adjusted/reduced aggregate video content is of a size less than apredetermined threshold. In some embodiments, the predeterminedthreshold can be configured by server 232, or the user. In otherembodiments, the predetermined threshold can be identifies by a userprevious behavior patterns in reviewing adjusted aggregate videocontent. That is, the premises device 219 and 229 can average the amountof time a user has reviewed adjusted aggregate video content in the pastand configure the predetermined threshold that correspond to the averageamount of time needed for the user to review. For example, previously,the premises device 219 and 229 has recorded that a user can only spend10 minutes at a time to review adjusted aggregate video content. Thus,the premises device 219 and 229 can configure the predeterminedthreshold to a size of the adjusted aggregate video contentcorresponding to 10 minutes of review time. In some embodiments, thepremises device 219 and 229 can determine that the aggregate videocontent cannot be adjusted or reduced to be a size lower than thepredetermined threshold. Thus, an alarm notification can be sent to acommunication device 213 of the user notifying that the size of theadjusted aggregate video content is more than the predeterminedthreshold.

In one or more embodiments, the adjusted or reduced aggregate videocontent is presented to the user on the communication device 213. Theadjusted aggregate video content includes a set of images for the userto review. The user, via a user interface, provides identifications forthe set images. For example, an image can be of a new neighbor. Thus,the user provides identification information for the image that theperson in the image is the new neighbor.

In one or more embodiments, the training model is adjusted based on theidentifications for the set of images. Thus, for example, when theadjusted training model is applied to images in any aggregate videocontent in the future, the premises device 219 and 229 would be able toidentify the new neighbor and discard images of the new neighbor whenadjusting any future aggregate video content. Further, the adjustedtraining model is provided to the server 232. Thus, if the adjustedtraining model is provided by premises device 219, then the server canshare the adjusted training model with premises device 229 associatedwith another neighbor to identify the new neighbor when applied to anyaggregate video content in the future. In other embodiments, thepremises device 219 and 229 can generate a new training model based onthe identification information for the images and provide the newtraining model to the server 232. Further, the server 232 can share thenew training model with other premise devices.

The training models can utilize several techniques to adjust or reducethe aggregate video content. These techniques include using one or anycombination of supervised machine learning, video clustering, and activelearning. Such techniques incorporate the identifications of the imagesprovided in the user-generated input to adjust/reduce future aggregatevideo content. Additional techniques, such as supervised machinelearning, can include presenting representative portions of theaggregate video content to the user. Moreover, the user can associateeach representative portion to either a pre-defined event or a newevent, thereby generating a new training model or adjusting an existingtraining model. That is, if any future aggregate video content containsportions similar to the representative portion, then the premises device219 and 229 can classify the portion to the pre-defined event or newevent, accordingly. In using video clustering techniques, similarportions of the aggregate video content are grouped together.Representative examples of each group are presented to user to reviewinstead of the entirety of the group, thereby lessening the user'sreview. In using active learning techniques, representative examples ofportions of the aggregate video content are selected. Theserepresentative examples are called support vectors. Support vectormachines (SVM) can be used to determine support vectors. Further,support vector machines can be used to generate supervised trainingmodels based on training examples. Applying such models to the aggregatevideo content classifies events into categories according to thetraining examples. Within supervised machine learning, video clustering,and active learning, further techniques can be used to adjust/reduce theaggregate video content. For example, scale-invariant feature transformscan be used to detect and describe local features in images to detectwhich images within the captured video content contain an event. Afurther example can be using spatiotemporal interest point techniquesthat detect action or motion within images to assist in detecting eventswithin the aggregate video content.

FIGS. 3-7 depict illustrative embodiments of user interfaces that areused in systems for aggregating video content in FIGS. 1-2. Referring toFIG. 3, the premises device 219 can present images of adjusted aggregatevideo content on a user interface 301 for a user to review on thecommunication device 213. An image 302 can include an image of a person114. Further, the user interface 300 may also include boxes 306 and 310that can be checked to discard 304 or keep 308 the image 302 in whenadjusting aggregate video content in the future. For example, the person114 can be the neighborhood mailman. The user can identify the person114 is known and indicate, via the user interface 300. Further, based onthe user input and the identification of the person 114, the trainingmodel applied to the aggregate video content is adjusted. Thus, whenapplying the adjusted training model to any future aggregate videocontent, an image of person 114 within any future aggregate videocontent is discarded. This makes the review any future aggregate videocontent less cumbersome to the user.

Referring to FIG. 4, the premises device 219 can present images ofadjusted aggregate video content on a user interface 401 for a user toreview on the communication device 213. An image 402 can include animage of a person 122. Further, the user interface 400 may also includeboxes 406 and 410 that can be checked to discard 404 or keep 408 theimage 402 in when adjusting aggregate video content in the future. Forexample, the person 122 can be a stranger that the user does not knowand finds suspicious. Thus, when applying the adjusted training model toany future aggregate video content, an image of person 122 within anyfuture aggregate video content is kept to be reviewed by the user.

Referring to FIG. 5, a user interface 500 on the communication device213 presents an image 502 of a person. The image 502 can be captured bya camera communicatively coupled to the communication device 213 orotherwise provided to the communication device 213. Further, userinterface 500 includes boxes 506 and 510 that can be checked to uploadthe image 502 to the premises device 219 or to server 232. In addition,the user interface 500 allows the user to indicate whether to discard514 or keep 520 images of person 512 using a check boxes 516 and 520 inadjusting of any future aggregate video content. For example, if person512 is the new nanny for the neighbor, the user can indicate to discardimages containing person 512 in any future aggregate video content. Inanother example, if person 512 is a suspected criminal, the user canindicate to keep images containing person 512 in any future aggregatevideo content for the user to review. The premises device 219,responsive to receiving the image 502 adjusts the training model(s) thatwould be applied to any future aggregate video content, accordingly asdescribed herein.

Referring to FIG. 6, a user interface 600 can be presented on thecommunication device 213 for a user to select one or more trainingmodels 604, 608, 612, 624, 628, and 632 using check boxes 606, 610, 614,626, 630, and 634. For example, if the user is selecting training modelsto be applied to aggregate video content captured at a premises in anurban environment, then the user can select a training model associatedwith an urban environment. Such a training model can discard images thatare typically found in urban environments when adjusting aggregate videocontent for the user to review. For example, the training model candiscard images for the user to review that contain of parked taxi cabsin front of the premises. Further, the user can select training modelsassociated with the user's neighbor 624, brother 628, and son 632. Suchtraining models can include discarding images of people within thehouseholds of the neighbor, brother, and son in adjustment of any futureaggregate video content. After selecting the training models, the usercan save 640 or cancel 642 the selections. After the selected trainingmodels are saved, the premises device 219 can apply the selectedtraining models in adjusting any future aggregate video content.

Referring to FIG. 7, a user interface 700 can present a list ofcharacteristics of a premises for a user to select using check boxes.706, 710, 714, 726, 730, and 734. These characteristics can include thepremises being rural 704, suburban 708, urban 712, a government building724, office 728, or a home 732. After selecting the characteristics, theuser can save 740 or cancel 742 the selections. After thecharacteristics are saved, the characteristics are provided to thepremises device 219 or to the server 232. The premises device 219 or theserver 232 can select a training model according to the savedcharacteristics, and apply the selected training model in adjusting anyfuture aggregate video content.

FIG. 8 depicts an illustrative embodiment of a method 800 used bysystems 100 and 200 in FIGS. 1-2. At a step 804, the method 800 caninclude receiving video content from each of a multiple of camerasoriented toward a premises by a premises device 219 resulting inmultiple video content. The multiple video content comprises images ofmultiple events. At step 832, the method 800 can also includeaggregating the multiple video content by the premises device 219. Priorto aggregating the video content, at step 808, the method 800 caninclude receiving multiple, selectable training models from a server 232by premises device 219. In some embodiment, at least one of theselectable training models is generated by the premises device 229 of athird party premises associated with the current premises (e.g.neighbor, parent, children, sibling, etc.). At a step 812, the method800 can include providing a list of the multiple selectable trainingmodels to the user interface on the communication device 213 by thepremises device 219. Further, at step 816, the method 800 can includeobtaining an indication of the selected training model from the list ofthe plurality of selectable training models via the user interface bythe premises device.

At a step 820, the method 800 can include identifying a plurality ofcharacteristics for the current premises by the premises device. Forexample, the premises device can provide a list of selectablecharacteristics of the premises on a user interface of the communicationdevice 213 to the user. Further, the user can select the characteristicsthat apply to the premises on the user interface and the user interfaceprovides the selected characteristics to the premises device 219. Atstep 824, the method 800 can include providing the plurality ofcharacteristics to the server 232 by the premises device 219. Inaddition, at step 828, the method 800 can include receiving the selectedtraining model from the server 232 according to the plurality ofcharacteristics by the premises device 219.

At step 836, the method 800 can include applying the selected trainingmodel to adjust the aggregate video content by the premises device 219.The adjusted aggregate video content comprises a first subset of theimages and does not comprise a second subset of the images from theaggregate video content. Further, the first subset of the images isdetermined by the selected training model based on a plurality ofcategories corresponding to the plurality of events. The method 800, atstep 840, can include determining, by the premises device 219, whether asize of the adjusted aggregate video content is above a predeterminedthreshold. If so, then the method 800 can include applying anothertraining model to adjust or reduce the size of the aggregate videocontent by the premises device 219. If not, then the method 800, at step844, can proceed to presenting, by the premises device 219, the adjustedaggregate video content on a user interface of the communication devicefor the user to review. At step 848, the method 800 can also includereceiving user-generated input for the adjusted aggregate video contentby the premises device 219. The user-generated input can provideidentifications for the first subset of the images in the adjustedaggregate video content. At step 852, the method 800 can further includeadjusting the selected training model according to the user-generatedinput by the premises device 219. At step 860, the method 800 canadditionally include providing the adjusted training model to the server232 by the premises device 219.

At step 856, the method 800 can include generating, by the premisesdevice 219, a new training model according to the identifications forthe first subset of the images. At step 872, the method 800 includes theserver 232 receiving the new training model from the premises device219.

Further, at step 854, the method 800 can include receiving updateinformation for the plurality of selectable training models by thepremises device 219 from a user interface on the communication device213. At step 858, the method 800 can include providing the updateinformation to the server 232 by premises device 219. In addition, atstep 872, the method 800 include the server 232 receiving the updateinformation. The server can modify the plurality of selectable trainingmodels according to the update information.

While for purposes of simplicity of explanation, the respectiveprocesses are shown and described as a series of blocks in FIG. 8, it isto be understood and appreciated that the claimed subject matter is notlimited by the order of the blocks, as some blocks may occur indifferent orders and/or concurrently with other blocks from what isdepicted and described herein. Moreover, not all illustrated blocks maybe required to implement the methods described herein.

FIG. 9 depicts an illustrative embodiment of a first communicationsystem 900 for delivering video content. The communication system 900can represent an Internet Protocol Television (IPTV) media system.Communication system 900 can be overlaid or operably coupled with system100 and 200 of FIGS. 1 and 2 as another representative embodiment ofcommunication system 900. For instance, one or more devices 906 and/or907 illustrated in the communication system 900 of FIG. 9 can aggregatevideo content and adjust the aggregate video content according to atraining model. The adjusted aggregate video content comprises a firstsubset of the images and does not comprise a second subset of the imagesfrom the aggregate video content. The first subset of the images isdetermined by the training model based on multiple categoriescorresponding to multiple events. The training model can be provided todevice 906 and/or 907 by servers 930. Devices such as 908 and 916 canpresent the adjusted aggregate video content and receivingidentifications for the first subset of the images in the aggregatevideo content via user-generated input. Further, devices 906 and/or 907can adjust the training model according to the identifications andprovide the adjusted training model to servers 930.

The IPTV media system can include a super head-end office (SHO) 910 withat least one super headend office server (SHS) 911 which receives videocontent from satellite and/or terrestrial communication systems. In thepresent context, media content can represent, for example, audiocontent, moving image content such as 2D or 3D videos, video games,virtual reality content, still image content, and combinations thereof.The SHS server 911 can forward packets associated with the media contentto one or more video head-end servers (VHS) 414 via a network of videohead-end offices (VHO) 912 according to a multicast communicationprotocol.

The VHS 914 can distribute multimedia broadcast content via an accessnetwork 918 to commercial and/or residential buildings 902 housing agateway 904 (such as a residential or commercial gateway). The accessnetwork 918 can represent a group of digital subscriber line accessmultiplexers (DSLAMs) located in a central office or a service areainterface that provide broadband services over fiber optical links orcopper twisted pairs 919 to buildings 902. The gateway 904 can usecommunication technology to distribute broadcast signals to mediaprocessors 906 such as Set-Top Boxes (STBs) which in turn presentbroadcast channels to media devices 908 such as computers or televisionsets managed in some instances by a media controller 907 (such as aninfrared or RF remote controller).

The gateway 904, the media processors 906, and media devices 908 canutilize tethered communication technologies (such as coaxial, powerlineor phone line wiring) or can operate over a wireless access protocolsuch as Wireless Fidelity (WiFi), Bluetooth®, Zigbee®, or other presentor next generation local or personal area wireless network technologies.By way of these interfaces, unicast communications can also be invokedbetween the media processors 906 and subsystems of the IPTV media systemfor services such as video-on-demand (VoD), browsing an electronicprogramming guide (EPG), or other infrastructure services.

A satellite broadcast television system 929 can be used in the mediasystem of FIG. 9. The satellite broadcast television system can beoverlaid, operably coupled with, or replace the IPTV system as anotherrepresentative embodiment of communication system 900. In thisembodiment, signals transmitted by a satellite 915 that include mediacontent can be received by a satellite dish receiver 931 coupled to thebuilding 902. Modulated signals received by the satellite dish receiver931 can be transferred to the media processors 906 for demodulating,decoding, encoding, and/or distributing broadcast channels to the mediadevices 908. The media processors 906 can be equipped with a broadbandport to an Internet Service Provider (ISP) network 932 to enableinteractive services such as VoD and EPG as described above.

In yet another embodiment, an analog or digital cable broadcastdistribution system such as cable TV system 933 can be overlaid,operably coupled with, or replace the IPTV system and/or the satelliteTV system as another representative embodiment of communication system900. In this embodiment, the cable TV system 933 can also provideInternet, telephony, and interactive media services. System 900 enablesvarious types of interactive television and/or services including IPTV,cable and/or satellite.

The subject disclosure can apply to other present or next generationover-the-air and/or landline media content services system.

Some of the network elements of the IPTV media system can be coupled toone or more computing devices 930, a portion of which can operate as aweb server for providing web portal services over the ISP network 932 towireline media devices 908 or wireless communication devices 916.

Communication system 900 can also provide for all or a portion of thecomputing devices 930 to function as a network device or server thatmanages training models for a group of premises. For instance, function962 of server 930 can be similar to the functions described for server232 of FIG. 2 in accordance with method 800 of FIG. 8. The server 930can use computing and communication technology to perform function of atraining model manager 962, which can include among other things, havingaccess to training models from a database, receiving and storingtraining models generated or adjusted by premises, providing the storedtraining models, sharing training models from other premises. Further,the server 930 can receive characteristics of the premises to adjuststored training models. In addition, the server 930 can receiveuser-generated information such as images of persons to update thestored training model. The media processors 906 and wirelesscommunication devices 916 can be provisioned with software functions 964and 966, respectively, to utilize the services of server 930. Forinstance, functions 964 and 964 of media processors 906 and wirelesscommunication devices 916 can be similar to the functions described forthe premises device 219 and 229 as well communication device 213 of FIG.2 in accordance with method 800 of FIG. 8.

Multiple forms of media services can be offered to media devices overlandline technologies such as those described above. Additionally, mediaservices can be offered to media devices by way of a wireless accessbase station 917 operating according to common wireless access protocolssuch as Global System for Mobile or GSM, Code Division Multiple Accessor CDMA, Time Division Multiple Access or TDMA, Universal MobileTelecommunications or UMTS, World interoperability for Microwave orWiMAX, Software Defined Radio or SDR, Long Term Evolution or LTE, and soon. Other present and next generation wide area wireless access networktechnologies can be used in one or more embodiments of the subjectdisclosure.

FIG. 10 depicts an illustrative embodiment of a communication system1000 employing an IP Multimedia Subsystem (IMS) network architecture tofacilitate the combined services of circuit-switched and packet-switchedsystems. Communication system 1000 can be overlaid or operably coupledwith system 100 and 200 of FIGS. 1 and/or 2 and communication system 900as another representative embodiment of communication system 900.Application servers can aggregate video content and adjust the aggregatevideo content according to a training model. The training model can begenerated by the application server according to user-generated input orprovided by server 930. The adjusted aggregate video content comprises afirst subset of the images and does not comprise a second subset of theimages from the aggregate video content. The first subset of the imagesis determined by the training model based on a plurality of categoriescorresponding to a plurality of events. Communication device 1005 and1002 can present the adjusted aggregate video content and provideidentifications to the application servers 1017 for the first subset ofthe images in the aggregate video content. Further, the applicationservers 1017 can adjust the training model according to theidentifications and provide the adjusted training model to server 930.

Communication system 1000 can comprise a Home Subscriber Server (HSS)1040, a tElephone NUmber Mapping (ENUM) server 1030, and other networkelements of an IMS network 1050. The IMS network 1050 can establishcommunications between IMS-compliant communication devices (CDs) 1001,1002, Public Switched Telephone Network (PSTN) CDs 1003, 1005, andcombinations thereof by way of a Media Gateway Control Function (MGCF)1020 coupled to a PSTN network 1060. The MGCF 1020 need not be used whena communication session involves IMS CD to IMS CD communications. Acommunication session involving at least one PSTN CD may utilize theMGCF 1020.

IMS CDs 1001, 1002 can register with the IMS network 1050 by contactinga Proxy Call Session Control Function (P-CSCF) which communicates withan interrogating CSCF (I-CSCF), which in turn, communicates with aServing CSCF (S-CSCF) to register the CDs with the HSS 1040. To initiatea communication session between CDs, an originating IMS CD 1001 cansubmit a Session Initiation Protocol (SIP INVITE) message to anoriginating P-CSCF 1004 which communicates with a correspondingoriginating S-CSCF 1006. The originating S-CSCF 1006 can submit the SIPINVITE message to one or more application servers (ASs) 1017 that canprovide a variety of services to IMS subscribers.

For example, the application servers 1017 can be used to performoriginating call feature treatment functions on the calling party numberreceived by the originating S-CSCF 1006 in the SIP INVITE message.Originating treatment functions can include determining whether thecalling party number has international calling services, call IDblocking, calling name blocking, 7-digit dialing, and/or is requestingspecial telephony features (e.g., *72 forward calls, *73 cancel callforwarding, *67 for caller ID blocking, and so on). Based on initialfilter criteria (iFCs) in a subscriber profile associated with a CD, oneor more application servers may be invoked to provide various calloriginating feature services.

Additionally, the originating S-CSCF 1006 can submit queries to the ENUMsystem 1030 to translate an E.164 telephone number in the SIP INVITEmessage to a SIP Uniform Resource Identifier (URI) if the terminatingcommunication device is IMS-compliant. The SIP URI can be used by anInterrogating CSCF (I-CSCF) 1007 to submit a query to the HSS 1040 toidentify a terminating S-CSCF 1014 associated with a terminating IMS CDsuch as reference 1002. Once identified, the I-CSCF 1007 can submit theSIP INVITE message to the terminating S-CSCF 1014. The terminatingS-CSCF 1014 can then identify a terminating P-CSCF 1016 associated withthe terminating CD 1002. The P-CSCF 1016 may then signal the CD 1002 toestablish Voice over Internet Protocol (VoIP) communication services,thereby enabling the calling and called parties to engage in voiceand/or data communications. Based on the iFCs in the subscriber profile,one or more application servers may be invoked to provide various callterminating feature services, such as call forwarding, do not disturb,music tones, simultaneous ringing, sequential ringing, etc.

In some instances the aforementioned communication process issymmetrical. Accordingly, the terms “originating” and “terminating” inFIG. 10 may be interchangeable. It is further noted that communicationsystem 1000 can be adapted to support video conferencing. In addition,communication system 1000 can be adapted to provide the IMS CDs 1001,1002 with the multimedia and Internet services of communication system900 of FIG. 9.

If the terminating communication device is instead a PSTN CD such as CD1003 or CD 1005 (in instances where the cellular phone only supportscircuit-switched voice communications), the ENUM system 1030 can respondwith an unsuccessful address resolution which can cause the originatingS-CSCF 1006 to forward the call to the MGCF 1020 via a Breakout GatewayControl Function (BGCF) 519. The MGCF 1020 can then initiate the call tothe terminating PSTN CD over the PSTN network 1060 to enable the callingand called parties to engage in voice and/or data communications.

It is further appreciated that the CDs of FIG. 10 can operate aswireline or wireless devices. For example, the CDs of FIG. 10 can becommunicatively coupled to a cellular base station 1021, a femtocell, aWiFi router, a Digital Enhanced Cordless Telecommunications (DECT) baseunit, or another suitable wireless access unit to establishcommunications with the IMS network 1050 of FIG. 10. The cellular accessbase station 1021 can operate according to common wireless accessprotocols such as GSM, CDMA, TDMA, UMTS, WiMax, SDR, LTE, and so on.Other present and next generation wireless network technologies can beused by one or more embodiments of the subject disclosure. Accordingly,multiple wireline and wireless communication technologies can be used bythe CDs of FIG. 10.

Cellular phones supporting LTE can support packet-switched voice andpacket-switched data communications and thus may operate asIMS-compliant mobile devices. In this embodiment, the cellular basestation 1021 may communicate directly with the IMS network 1050 as shownby the arrow connecting the cellular base station 521 and the P-CSCF1016.

Alternative forms of a CSCF can operate in a device, system, component,or other form of centralized or distributed hardware and/or software.Indeed, a respective CSCF may be embodied as a respective CSCF systemhaving one or more computers or servers, either centralized ordistributed, where each computer or server may be configured to performor provide, in whole or in part, any method, step, or functionalitydescribed herein in accordance with a respective CSCF. Likewise, otherfunctions, servers and computers described herein, including but notlimited to, the HSS, the ENUM server, the BGCF, and the MGCF, can beembodied in a respective system having one or more computers or servers,either centralized or distributed, where each computer or server may beconfigured to perform or provide, in whole or in part, any method, step,or functionality described herein in accordance with a respectivefunction, server, or computer.

The server 930 of FIG. 9 can be operably coupled to communication system1000 for purposes similar to those described above. Server 930 canperform function 962 and thereby provide training models to applicationservers 1017 to adjust aggregate video content and then present theadjusted aggregate video content to the CDs 1001, 1002, 1003 and 1005 ofFIG. 10, similar to the functions described for premises devices 219 and229 and server 232 of FIG. 2 in accordance with method 800 of FIG. 8.CDs 1001, 1002, 1003 and 1005, which can be adapted with software toperform function 1072 to utilize the services of the premises devices219 and 229 as well as server 930 similar to the functions described forcommunication device 213 of FIG. 2 in accordance with method 800 of FIG.8. Server 930 can be an integral part of the application server(s) 1017performing function 1074, which can be substantially similar to function962 and adapted to the operations of the IMS network 1050.

For illustration purposes only, the terms S-CSCF, P-CSCF, I-CSCF, and soon, can be server devices, but may be referred to in the subjectdisclosure without the word “server.” It is also understood that anyform of a CSCF server can operate in a device, system, component, orother form of centralized or distributed hardware and software. It isfurther noted that these terms and other terms such as DIAMETER commandsare terms can include features, methodologies, and/or fields that may bedescribed in whole or in part by standards bodies such as 3^(rd)Generation Partnership Project (3GPP). It is further noted that some orall embodiments of the subject disclosure may in whole or in partmodify, supplement, or otherwise supersede final or proposed standardspublished and promulgated by 3GPP.

FIG. 11 depicts an illustrative embodiment of a web portal 1102 of acommunication system 1100. Communication system 1100 can be overlaid oroperably coupled with systems 100 and 200 of FIGS. 1 and 2,communication system 900, and/or communication system 1000 as anotherrepresentative embodiment of systems 200 and 200 of FIGS. 1 and 2,communication system 900, and/or communication system 1000. The webportal 1102 can be used for managing services of aggregating capturedvideo content and adjusting the aggregate video content by systems 100and 200 of FIGS. 1 and 2 and communication systems 900-10000. A web pageof the web portal 1102 can be accessed by a Uniform Resource Locator(URL) with an Internet browser using an Internet-capable communicationdevice such as those described in FIG. 2 and FIGS. 9-10. The web portal1102 can be configured, for example, to access a media processor 906 andservices managed thereby such as a Digital Video Recorder (DVR), a Videoon Demand (VoD) catalog, an Electronic Programming Guide (EPG), or apersonal catalog (such as personal videos, pictures, audio recordings,etc.) stored at the media processor 906. The web portal 1102 can also beused for provisioning IMS services described earlier, provisioningInternet services, provisioning cellular phone services, and so on.

The web portal 1102 can further be utilized to manage and provisionsoftware applications 962-966, and 1072-1074 to adapt these applicationsas may be desired by subscribers and/or service providers of systems 100and 200 of FIGS. 1 and 2, and communication systems 900-1000. Forinstance, users of services for managing captured video content fromsurveillance cameras provided by server 232 or server 930 can log intotheir on-line accounts and provision the premises devices 219 and 229 aswell server 232 or server 930 with characteristics of the premises,images objects including persons to adjust training models applied tothe aggregate video content, a predetermined threshold of the size ofadjusted video content to review and so on. Service providers can logonto an administrator account to provision, monitor and/or maintain thesystems 100 and 299 of FIGS. 1 and 2 or server 930.

FIG. 12 depicts an illustrative embodiment of a communication device1200. Communication device 1200 can serve in whole or in part as anillustrative embodiment of the premises devices 219 and 2219 as well ascommunication device 213 depicted in FIG. 2, and FIGS. 9-10 and can beconfigured to perform portions of method 800 of FIG. 3.

Communication device 1200 can comprise a wireline and/or wirelesstransceiver 1202 (herein transceiver 1202), a user interface (UI) 1204,a power supply 1214, a location receiver 1216, a motion sensor 1218, anorientation sensor 1220, and a controller 1206 for managing operationsthereof. The transceiver 1202 can support short-range or long-rangewireless access technologies such as Bluetooth®, ZigBee®, WiFi, DECT, orcellular communication technologies, just to mention a few (Bluetooth®and ZigBee® are trademarks registered by the Bluetooth® Special InterestGroup and the ZigBee® Alliance, respectively). Cellular technologies caninclude, for example, CDMA-1X, UMTS/HSDPA, GSM/GPRS, TDMA/EDGE, EV/DO,WiMAX, SDR, LTE, as well as other next generation wireless communicationtechnologies as they arise. The transceiver 1202 can also be adapted tosupport circuit-switched wireline access technologies (such as PSTN),packet-switched wireline access technologies (such as TCP/IP, VoIP,etc.), and combinations thereof.

The UI 1204 can include a depressible or touch-sensitive keypad 1208with a navigation mechanism such as a roller ball, a joystick, a mouse,or a navigation disk for manipulating operations of the communicationdevice 1200. The keypad 1208 can be an integral part of a housingassembly of the communication device 1200 or an independent deviceoperably coupled thereto by a tethered wireline interface (such as a USBcable) or a wireless interface supporting for example Bluetooth®. Thekeypad 1208 can represent a numeric keypad commonly used by phones,and/or a QWERTY keypad with alphanumeric keys. The UI 1204 can furtherinclude a display 1210 such as monochrome or color LCD (Liquid CrystalDisplay), OLED (Organic Light Emitting Diode) or other suitable displaytechnology for conveying images to an end user of the communicationdevice 1200. In an embodiment where the display 1210 is touch-sensitive,a portion or all of the keypad 1208 can be presented by way of thedisplay 1210 with navigation features.

The display 1210 can use touch screen technology to also serve as a userinterface for detecting user input. As a touch screen display, thecommunication device 1200 can be adapted to present a user interfacewith graphical user interface (GUI) elements that can be selected by auser with a touch of a finger. The touch screen display 1210 can beequipped with capacitive, resistive or other forms of sensing technologyto detect how much surface area of a user's finger has been placed on aportion of the touch screen display. This sensing information can beused to control the manipulation of the GUI elements or other functionsof the user interface. The display 1210 can be an integral part of thehousing assembly of the communication device 1200 or an independentdevice communicatively coupled thereto by a tethered wireline interface(such as a cable) or a wireless interface.

The UI 1204 can also include an audio system 1212 that utilizes audiotechnology for conveying low volume audio (such as audio heard inproximity of a human ear) and high volume audio (such as speakerphonefor hands free operation). The audio system 1212 can further include amicrophone for receiving audible signals of an end user. The audiosystem 1212 can also be used for voice recognition applications. The UI1204 can further include an image sensor 1213 such as a charged coupleddevice (CCD) camera for capturing still or moving images.

The power supply 1214 can utilize common power management technologiessuch as replaceable and rechargeable batteries, supply regulationtechnologies, and/or charging system technologies for supplying energyto the components of the communication device 1200 to facilitatelong-range or short-range portable applications. Alternatively, or incombination, the charging system can utilize external power sources suchas DC power supplied over a physical interface such as a USB port orother suitable tethering technologies.

The location receiver 1216 can utilize location technology such as aglobal positioning system (GPS) receiver capable of assisted GPS foridentifying a location of the communication device 1200 based on signalsgenerated by a constellation of GPS satellites, which can be used forfacilitating location services such as navigation. The motion sensor1218 can utilize motion sensing technology such as an accelerometer, agyroscope, or other suitable motion sensing technology to detect motionof the communication device 1200 in three-dimensional space. Theorientation sensor 1220 can utilize orientation sensing technology suchas a magnetometer to detect the orientation of the communication device1200 (north, south, west, and east, as well as combined orientations indegrees, minutes, or other suitable orientation metrics).

The communication device 1200 can use the transceiver 1202 to alsodetermine a proximity to a cellular, WiFi, Bluetooth®, or other wirelessaccess points by sensing techniques such as utilizing a received signalstrength indicator (RSSI) and/or signal time of arrival (TOA) or time offlight (TOF) measurements. The controller 1206 can utilize computingtechnologies such as a microprocessor, a digital signal processor (DSP),programmable gate arrays, application specific integrated circuits,and/or a video processor with associated storage memory such as Flash,ROM, RAM, SRAM, DRAM or other storage technologies for executingcomputer instructions, controlling, and processing data supplied by theaforementioned components of the communication device 1200.

Other components not shown in FIG. 12 can be used in one or moreembodiments of the subject disclosure. For instance, the communicationdevice 1200 can include a reset button (not shown). The reset button canbe used to reset the controller 1206 of the communication device 1200.In yet another embodiment, the communication device 1200 can alsoinclude a factory default setting button positioned, for example, belowa small hole in a housing assembly of the communication device 1200 toforce the communication device 1200 to re-establish factory settings. Inthis embodiment, a user can use a protruding object such as a pen orpaper clip tip to reach into the hole and depress the default settingbutton. The communication device 1200 can also include a slot for addingor removing an identity module such as a Subscriber Identity Module(SIM) card. SIM cards can be used for identifying subscriber services,executing programs, storing subscriber data, and so forth.

The communication device 1200 as described herein can operate with moreor less of the circuit components shown in FIG. 12. These variantembodiments can be used in one or more embodiments of the subjectdisclosure.

The communication device 1200 can be adapted to perform the functions ofpremises devices 219 and 229 as well as communication device 213 of FIG.2, the media processor 906, the media devices 908, or the portablecommunication devices 916 of FIG. 9, as well as the IMS CDs 1001-1002and PSTN CDs 1003-1005 of FIG. 5. It will be appreciated that thecommunication device 1200 can also represent other devices that canoperate in systems 100 and 200 of FIGS. 1 and 2, communication systems900-1000 of FIGS. 9-12 such as a gaming console and a media player. Inaddition, the controller 1206 can be adapted in various embodiments toperform the functions 962-966 and 1072-1074, respectively.

Upon reviewing the aforementioned embodiments, it would be evident to anartisan with ordinary skill in the art that said embodiments can bemodified, reduced, or enhanced without departing from the scope of theclaims described below. For example, a person of ordinary skill in theart would understand to combine portions of some embodiments withportions of other embodiments. Further, portions of embodiments can alsobe implemented. Other embodiments can be used in the subject disclosure.

It should be understood that devices described in the exemplaryembodiments can be in communication with each other via various wirelessand/or wired methodologies. The methodologies can be links that aredescribed as coupled, connected and so forth, which can includeunidirectional and/or bidirectional communication over wireless pathsand/or wired paths that utilize one or more of various protocols ormethodologies, where the coupling and/or connection can be direct (e.g.,no intervening processing device) and/or indirect (e.g., an intermediaryprocessing device such as a router).

FIG. 13 depicts an exemplary diagrammatic representation of a machine inthe form of a computer system 1300 within which a set of instructions,when executed, may cause the machine to perform any one or more of themethods described above. One or more instances of the machine canoperate, for example, as the premise devices 219 and 229, server 232,communication device 213 and server 930, the media processor 906,communication devices 908, 916, 1005, and 1002 and other devices ofFIGS. 1-12. In some embodiments, the machine may be connected (e.g.,using a network) to other machines. In a networked deployment, themachine may operate in the capacity of a server or a client user machinein a server-client user network environment, or as a peer machine in apeer-to-peer (or distributed) network environment.

The machine may comprise a server computer, a client user computer, apersonal computer (PC), a tablet, a smart phone, a laptop computer, adesktop computer, a control system, a network router, switch or bridge,or any machine capable of executing a set of instructions (sequential orotherwise) that specify actions to be taken by that machine. It will beunderstood that a communication device of the subject disclosureincludes broadly any electronic device that provides voice, video ordata communication. Further, while a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methods discussed herein.

The computer system 1300 may include a processor (or controller) 1302(e.g., a central processing unit (CPU)), a graphics processing unit(GPU, or both), a main memory 1304 and a static memory 1306, whichcommunicate with each other via a bus 1308. The computer system 1300 mayfurther include a display unit 1310 (e.g., a liquid crystal display(LCD), a flat panel, or a solid state display). The computer system 1300may include an input device 1312 (e.g., a keyboard), a cursor controldevice 1314 (e.g., a mouse), a disk drive unit 1316, a signal generationdevice 1318 (e.g., a speaker or remote control) and a network interfacedevice 1320. In distributed environments, the embodiments described inthe subject disclosure can be adapted to utilize multiple display units1310 controlled by two or more computer systems 1300. In thisconfiguration, presentations described by the subject disclosure may inpart be shown in a first of the display units 1310, while the remainingportion is presented in a second of the display units 1310.

The disk drive unit 1316 may include a tangible computer-readablestorage medium 1322 on which is stored one or more sets of instructions(e.g., software 1324) embodying any one or more of the methods orfunctions described herein, including those methods illustrated above.The instructions 1324 may also reside, completely or at least partially,within the main memory 1304, the static memory 1306, and/or within theprocessor 1302 during execution thereof by the computer system 1300. Themain memory 1304 and the processor 1302 also may constitute tangiblecomputer-readable storage media.

Dedicated hardware implementations including, but not limited to,application specific integrated circuits, programmable logic arrays andother hardware devices can likewise be constructed to implement themethods described herein. Application specific integrated circuits andprogrammable logic array can use downloadable instructions for executingstate machines and/or circuit configurations to implement embodiments ofthe subject disclosure. Applications that may include the apparatus andsystems of various embodiments broadly include a variety of electronicand computer systems. Some embodiments implement functions in two ormore specific interconnected hardware modules or devices with relatedcontrol and data signals communicated between and through the modules,or as portions of an application-specific integrated circuit. Thus, theexample system is applicable to software, firmware, and hardwareimplementations.

In accordance with various embodiments of the subject disclosure, theoperations or methods described herein are intended for operation assoftware programs or instructions running on or executed by a computerprocessor or other computing device, and which may include other formsof instructions manifested as a state machine implemented with logiccomponents in an application specific integrated circuit or fieldprogrammable gate array. Furthermore, software implementations (e.g.,software programs, instructions, etc.) including, but not limited to,distributed processing or component/object distributed processing,parallel processing, or virtual machine processing can also beconstructed to implement the methods described herein. Distributedprocessing environments can include multiple processors in a singlemachine, single processors in multiple machines, and/or multipleprocessors in multiple machines. It is further noted that a computingdevice such as a processor, a controller, a state machine or othersuitable device for executing instructions to perform operations ormethods may perform such operations directly or indirectly by way of oneor more intermediate devices directed by the computing device.

While the tangible computer-readable storage medium 1322 is shown in anexample embodiment to be a single medium, the term “tangiblecomputer-readable storage medium” should be taken to include a singlemedium or multiple media (e.g., a centralized or distributed database,and/or associated caches and servers) that store the one or more sets ofinstructions. The term “tangible computer-readable storage medium” shallalso be taken to include any non-transitory medium that is capable ofstoring or encoding a set of instructions for execution by the machineand that cause the machine to perform any one or more of the methods ofthe subject disclosure. The term “non-transitory” as in a non-transitorycomputer-readable storage includes without limitation memories, drives,devices and anything tangible but not a signal per se.

The term “tangible computer-readable storage medium” shall accordinglybe taken to include, but not be limited to: solid-state memories such asa memory card or other package that houses one or more read-only(non-volatile) memories, random access memories, or other re-writable(volatile) memories, a magneto-optical or optical medium such as a diskor tape, or other tangible media which can be used to store information.Accordingly, the disclosure is considered to include any one or more ofa tangible computer-readable storage medium, as listed herein andincluding art-recognized equivalents and successor media, in which thesoftware implementations herein are stored.

Although the present specification describes components and functionsimplemented in the embodiments with reference to particular standardsand protocols, the disclosure is not limited to such standards andprotocols. Each of the standards for Internet and other packet switchednetwork transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP) representexamples of the state of the art. Such standards are from time-to-timesuperseded by faster or more efficient equivalents having essentiallythe same functions. Wireless standards for device detection (e.g.,RFID), short-range communications (e.g., Bluetooth®, WiFi, Zigbee®), andlong-range communications (e.g., WiMAX, GSM, CDMA, LTE) can be used bycomputer system 1300. In one or more embodiments, information regardinguse of services can be generated including services being accessed,media consumption history, user preferences, and so forth. Thisinformation can be obtained by various methods including user input,detecting types of communications (e.g., video content vs. audiocontent), analysis of content streams, and so forth. The generating,obtaining and/or monitoring of this information can be responsive to anauthorization provided by the user.

The illustrations of embodiments described herein are intended toprovide a general understanding of the structure of various embodiments,and they are not intended to serve as a complete description of all theelements and features of apparatus and systems that might make use ofthe structures described herein. Many other embodiments will be apparentto those of skill in the art upon reviewing the above description. Theexemplary embodiments can include combinations of features and/or stepsfrom multiple embodiments. Other embodiments may be utilized and derivedtherefrom, such that structural and logical substitutions and changesmay be made without departing from the scope of this disclosure. Figuresare also merely representational and may not be drawn to scale. Certainproportions thereof may be exaggerated, while others may be minimized.Accordingly, the specification and drawings are to be regarded in anillustrative rather than a restrictive sense.

Although specific embodiments have been illustrated and describedherein, it should be appreciated that any arrangement which achieves thesame or similar purpose may be substituted for the embodiments describedor shown by the subject disclosure. The subject disclosure is intendedto cover any and all adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, can be used in the subject disclosure.For instance, one or more features from one or more embodiments can becombined with one or more features of one or more other embodiments. Inone or more embodiments, features that are positively recited can alsobe negatively recited and excluded from the embodiment with or withoutreplacement by another structural and/or functional feature. The stepsor functions described with respect to the embodiments of the subjectdisclosure can be performed in any order. The steps or functionsdescribed with respect to the embodiments of the subject disclosure canbe performed alone or in combination with other steps or functions ofthe subject disclosure, as well as from other embodiments or from othersteps that have not been described in the subject disclosure. Further,more than or less than all of the features described with respect to anembodiment can also be utilized.

Less than all of the steps or functions described with respect to theexemplary processes or methods can also be performed in one or more ofthe exemplary embodiments. Further, the use of numerical terms todescribe a device, component, step or function, such as first, second,third, and so forth, is not intended to describe an order or functionunless expressly stated so. The use of the terms first, second, thirdand so forth, is generally to distinguish between devices, components,steps or functions unless expressly stated otherwise. Additionally, oneor more devices or components described with respect to the exemplaryembodiments can facilitate one or more functions, where the facilitating(e.g., facilitating access or facilitating establishing a connection)can include less than every step needed to perform the function or caninclude all of the steps needed to perform the function.

In one or more embodiments, a processor (which can include a controlleror circuit) has been described that performs various functions. Itshould be understood that the processor can be multiple processors,which can include distributed processors or parallel processors in asingle machine or multiple machines. The processor can be used insupporting a virtual processing environment. The virtual processingenvironment may support one or more virtual machines representingcomputers, servers, or other computing devices. In such virtualmachines, components such as microprocessors and storage devices may bevirtualized or logically represented. The processor can include a statemachine, application specific integrated circuit, and/or programmablegate array including a Field PGA. In one or more embodiments, when aprocessor executes instructions to perform “operations”, this caninclude the processor performing the operations directly and/orfacilitating, directing, or cooperating with another device or componentto perform the operations.

The Abstract of the Disclosure is provided with the understanding thatit will not be used to interpret or limit the scope or meaning of theclaims. In addition, in the foregoing Detailed Description, it can beseen that various features are grouped together in a single embodimentfor the purpose of streamlining the disclosure. This method ofdisclosure is not to be interpreted as reflecting an intention that theclaimed embodiments require more features than are expressly recited ineach claim. Rather, as the following claims reflect, inventive subjectmatter lies in less than all features of a single disclosed embodiment.Thus the following claims are hereby incorporated into the DetailedDescription, with each claim standing on its own as a separately claimedsubject matter.

What is claimed is:
 1. A device, comprising: a processing systemincluding a processor; and a memory that stores executable instructionsthat, when executed by the processing system, facilitate performance ofoperations, comprising: receiving video content from each of a pluralityof cameras oriented toward a current premises resulting in a pluralityof video content, wherein the plurality of video content comprisesimages of a plurality of events; aggregating the plurality of videocontent to generate aggregate video content; applying a selectedtraining model to the aggregate video content resulting in adjustedaggregate video content, wherein the adjusted aggregate video contentcomprises a first subset of the images and does not comprise a secondsubset of the images, and wherein the first subset of the images isdetermined by the selected training model based on a plurality ofcategories corresponding to the plurality of events; presenting theadjusted aggregate video content; receiving user-generated input for theadjusted aggregate video content, wherein the user-generated inputprovides identifications for the first subset of the images in theaggregate video content; adjusting the selected training model accordingto the user-generated input resulting in an adjusted training model; andproviding the adjusted training model to a network device.
 2. The deviceof claim 1, wherein the applying of the selected training model to theaggregate video content further comprises analyzing the images of theplurality of events and classifying the images of the plurality ofevents into the plurality of categories.
 3. The device of claim 2,wherein the analyzing of the images of the plurality of events furthercomprises identifying a motion of an object in one of the images.
 4. Thedevice of claim 3, wherein the identifying the motion of the objectfurther comprises identifying the object as a person.
 5. The device ofclaim 4, wherein the classifying the images of the plurality of eventsfurther comprises determining whether the person is associated with thecurrent premises.
 6. The device of claim 5, wherein the determiningwhether the person is associated with current premises further comprisestransmitting an alarm notification responsive to determining that theperson is not associated with the current premises.
 7. The device ofclaim 5, wherein the determining whether the person is associated withcurrent premises further comprises using facial recognition.
 8. Thedevice of claim 1, wherein the operations further comprise: receiving aplurality of selectable training models from the network device, whereinat least one of the plurality of selectable training models is generatedby a premises device of a third party premises, and wherein the thirdparty premises is associated with the current premises; providing a listof the plurality of selectable training models to a user interface; andobtaining an indication of the selected training model from the list ofthe plurality of selectable training models via the user interface. 9.The device of claim 8, wherein the operations further comprise:receiving update information for the plurality of selectable trainingmodels; and providing the update information to the network device,wherein the network device modifies the plurality of selectable trainingmodels according to the update information.
 10. A machine-readablestorage medium, comprising executable instructions that, when executedby a processing system including a processor, facilitate performance ofoperations, comprising: receiving a plurality of video contentassociated with a current premises wherein the plurality of videocontent comprises images of a plurality of events; aggregating theplurality of video content to generate aggregate video content; applyinga selected training model to the aggregate video content resulting inadjusted aggregate video content, wherein the adjusted aggregate videocontent comprises a first subset of the images and does not comprise asecond subset of the images, and wherein the first subset of the imagesis determined by the selected training model based on a plurality ofcategories corresponding to the plurality of events, and wherein theselected training model is selected according to a plurality ofcharacteristics of the current premises; presenting the adjustedaggregate video content; receiving user-generated input for the adjustedaggregate video content, wherein the user-generated input providesidentifications for the first subset of the images in the aggregatevideo content; adjusting the selected training model according to theuser-generated input resulting in an adjusted training model; andproviding the adjusted training model to a network device.
 11. Themachine-readable storage medium of claim 10, wherein the applying of theselected training model to the aggregate video content further comprisesanalyzing the images of the plurality of events and classifying theimages of the plurality of events into the plurality of categories. 12.The machine-readable storage medium of claim 10, wherein the operationsfurther comprise: identifying a plurality of characteristics for thecurrent premises; providing the plurality of characteristics to thenetwork device; and receiving the selected training model from thenetwork device according to the plurality of characteristics.
 13. Themachine-readable storage medium of claim 12, wherein the network devicegenerates the selected training model from combining a plurality oftraining models according to the plurality of characteristics.
 14. Amethod, comprising: receiving, by a processing system including aprocessor, video content from each of a plurality of cameras orientedtoward a current premises resulting in a plurality of video content,wherein the plurality of video content comprises images of a pluralityof events; aggregating, by the processing system, the plurality of videocontent to generate aggregate video content; adjusting, by theprocessing system, the aggregate video content resulting in adjustedaggregate video content according to a training model, wherein theadjusted aggregate video content comprises a first subset of the imagesand does not comprise a second subset of the images, and wherein thefirst subset of the images is determined by the training model based ona plurality of categories corresponding to the plurality of events;presenting, by the processing system, the adjusted aggregate videocontent; receiving, by the processing system, identifications for thefirst subset of the images in the aggregate video content; adjusting, bythe processing system, the training model according to theidentifications resulting in an adjusted training model; and providing,by the processing system, the adjusted training model to a networkdevice.
 15. The method of claim 14, wherein the adjusting the aggregatevideo content further comprises analyzing, by the processing system, theimages of the plurality of events and classifying the images of theplurality of events into the plurality of categories.
 16. The method ofclaim 14, comprising generating, by the processing system, a newtraining model according to the identifications for the first subset ofthe images and providing the new training model to the network device.17. The method of claim 14, comprising determining, by the processingsystem, that a size of the adjusted aggregate video content is above apredetermined threshold.
 18. The method of claim 17, comprisingapplying, by the processing system, another training model to theaggregate video content to reduce the size of the adjusted aggregatevideo content is below the predetermined threshold.
 19. The method ofclaim 14, comprising receiving, by the processing system, the trainingmodel from a premises device associated with a third party premises viathe network device, wherein the training model is generated by thepremises device, and wherein the third party premises is associated withthe current premises.
 20. The method of claim 14, comprising updatingthe training model based on user-generated input comprising an image ofa person.